Prediction of antifreeze proteins (AFPs) holds significant importance due to their diverse applications in healthcare. Due to their unique freeze resistance property, AFPs have a wide range of applications, including food preservation, medicine, human cryosurgery, and the production of yoghurt. In this study, we have implement a robust strategy for AFP prediction by leveraging diverse approaches, including machine learning, sequence similarity, and pattern detection.
Reference: Kumar N., Choudhury S., Bajiya N., Patiyal S. and Raghava GPS (2024) Prediction of Anti-Freezing Proteins From Their Evolutionary Profile. Proteomics, doi.org/10.1002/pmic.202400157